82 search results - page 8 / 17 » Learning a ranking from pairwise preferences |
ECIR
2010
Springer
13 years 5 months ago
2010
Springer
Abstract. Machine learning ranking methods are increasingly applied to ranking tasks in information retrieval (IR). However ranking tasks in IR often differ from standard ranking t...
CORR
2006
Springer
13 years 7 months ago
2006
Springer
Clickthrough data is a particularly inexpensive and plentiful resource to obtain implicit relevance feedback for improving and personalizing search engines. However, it is well kn...
FSS
2008
13 years 7 months ago
2008
This paper introduces a new approach to classification which combines pairwise decomposition techniques with ideas and tools from fuzzy preference modeling. More specifically, our...
CIKM
2011
Springer
12 years 7 months ago
2011
Springer
Evaluating rankers using implicit feedback, such as clicks on documents in a result list, is an increasingly popular alternative to traditional evaluation methods based on explici...
SDM
2007
SIAM
13 years 8 months ago
2007
SIAM
The problem of combining the ranked preferences of many experts is an old and surprisingly deep problem that has gained renewed importance in many machine learning, data mining, a...